Multi-stage Financial Modeling using Machine Learning in R

Multi-stage Financial Modeling using Machine Learning in R

Multi-stage Financial Modeling using Machine Learning in R – I’ll be introducing multi-stage financial modeling R package to you. Let’s start with some background information. R package focuses on commodity price. So commodity, such as soybean, corn, cotton, their prices are always affected by different and many factors, such as economy, agriculture, weather, policies, you name it.

And you can find those information from different sources as well, such as news media, social media, government sites, and private companies. Since the related data are from different resources, you might have different granularities, such as some might be daily, some might be weekly, some might be annual, might have different formats.

And the data sets might be dirty. R package, financial modeling R, can help you reading the data, clean the data, and merge data with different granularities into one combined, clean temple data frame. And it also provides several data visualizations based on your data.

In addition, we also have an auto-machine learning pipeline, which helps you to inhabit parameters and pick the best model out of its. Now let’s see some examples of the outputs from the package. On the top half, from left to right, you can see a line plots of progress data, then you can see a correlation plots of extra cells.

Then it’s a time series plot, but with a politic events. Then, at last, you can see a word cloud of the tweets. At the bottom half, there’s a sample sequential model generated by R package. And that model gives 71% of the variation of deciding future price.

We also built a soybean contract dashboard. So this dashboard is an interactive way to give you some data visualizations based on the data you upload. It provides time series analysis, further analysis, and stock analysis based on your own preference.

You can use this dashboard for data visualization, as well as exploring the data sets, and getting some idea of feature selections and engineering. We recommend you do use it along with R package. So, I hope you’ll find R package helpful in some ways. Everything about R package is on GitHub, and you can assess our dashboard. Make sure to check it out.

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